Study on a Poisson's equation solver based on deep learning technique
暂无分享,去创建一个
Ji Wu | Fan Yang | Wei Tang | Maokun Li | Shenheng Xu | Tao Shan | Xunwang Dang | Maokun Li | Ji Wu | Fan Yang | Shenheng Xu | Xunwang Dang | Tao Shan | Wei Tang
[1] He Ming Yao,et al. Machine learning based MoM (ML-MoM) for parasitic capacitance extractions , 2016, 2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS).
[2] H. V. D. Vorst,et al. Model Order Reduction: Theory, Research Aspects and Applications , 2008 .
[3] Shenheng Xu,et al. Quasi-Periodic Array Modeling Using Reduced Basis Method , 2017 .
[4] Qi-Jun Zhang,et al. Artificial neural networks for RF and microwave design - from theory to practice , 2003 .
[5] Allen Taflove,et al. Computational Electrodynamics the Finite-Difference Time-Domain Method , 1995 .
[6] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[7] Ah Chung Tsoi,et al. Face recognition: a convolutional neural-network approach , 1997, IEEE Trans. Neural Networks.
[8] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[9] Roger F. Harrington,et al. Field computation by moment methods , 1968 .
[10] W. Marsden. I and J , 2012 .
[11] A. Ng. Feature selection, L1 vs. L2 regularization, and rotational invariance , 2004, Twenty-first international conference on Machine learning - ICML '04.
[12] Kyle Mills,et al. Deep learning and the Schrödinger equation , 2017, ArXiv.
[13] Michel Nakhla,et al. A neural network modeling approach to circuit optimization and statistical design , 1995 .
[14] Fan Yang,et al. Quasi-Periodic Array Modeling Using Reduced Basis Method , 2017, IEEE Antennas and Wireless Propagation Letters.
[15] 김덕영. [신간안내] Computational Electrodynamics (the finite difference time - domain method) , 2001 .
[16] Ahmed K. Noor,et al. Reduced Basis Technique for Nonlinear Analysis of Structures , 1979 .
[17] Niloy J. Mitra,et al. Learning A Physical Long-term Predictor , 2017, ArXiv.
[18] Wei Li,et al. Convolutional Neural Networks for Steady Flow Approximation , 2016, KDD.
[19] Gene H. Golub,et al. Matrix computations (3rd ed.) , 1996 .
[20] Rob Fergus,et al. Learning Physical Intuition of Block Towers by Example , 2016, ICML.
[21] Carla E. Brodley,et al. Proceedings of the twenty-first international conference on Machine learning , 2004, International Conference on Machine Learning.
[22] Ken Perlin,et al. Accelerating Eulerian Fluid Simulation With Convolutional Networks , 2016, ICML.
[23] Qi-Jun Zhang,et al. Neural Networks for RF and Microwave Design , 2000 .
[24] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[25] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[26] Robert H. Halstead,et al. Matrix Computations , 2011, Encyclopedia of Parallel Computing.
[27] Dieter Fox,et al. SE3-nets: Learning rigid body motion using deep neural networks , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[28] Carretera de Valencia,et al. The finite element method in electromagnetics , 2000 .
[29] R. Mittra,et al. Characteristic basis function method: A new technique for efficient solution of method of moments matrix equations , 2003 .
[30] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.